_SCREAMING_SNAKE_CASE 		=      """
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
"""

_SCREAMING_SNAKE_CASE 		=      [{"""type""": """code""", """content""": INSTALL_CONTENT}]
_SCREAMING_SNAKE_CASE 		=      {
    """{processor_class}""": """FakeProcessorClass""",
    """{model_class}""": """FakeModelClass""",
    """{object_class}""": """FakeObjectClass""",
}

import unittest

from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax

from .test_modeling_common_flax import FlaxModelTesterMixin


if is_flax_available():
     import jax
@require_flax
class SCREAMING_SNAKE_CASE_		(      __lowerCAmelCase  ,     unittest.TestCase		):
   __lowerCAmelCase           =				FlaxAutoencoderKL







   @property
   def 						lowerCamelCase_	(     self						:						Tuple				):





    """simple docstring"""


    UpperCamelCase			  =      4
    UpperCamelCase			  =      3
    UpperCamelCase			  =      (32, 32)

    UpperCamelCase			  =      jax.random.PRNGKey(0				)
    UpperCamelCase			  =      jax.random.uniform(lowerCamelCase_   ,   ((batch_size, num_channels) + sizes)				)

    return {"sample": image, "prng_key": prng_key}







   def 						lowerCamelCase_	(     self						:						str				):





    """simple docstring"""


    UpperCamelCase			  =      {
        """block_out_channels""": [32, 64],
        """in_channels""": 3,
        """out_channels""": 3,
        """down_block_types""": ["""DownEncoderBlock2D""", """DownEncoderBlock2D"""],
        """up_block_types""": ["""UpDecoderBlock2D""", """UpDecoderBlock2D"""],
        """latent_channels""": 4,
    }
    UpperCamelCase			  =      self.dummy_input
    return init_dict, inputs_dict
